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Causal Disentanglement for Semantics-Aware Intent Learning in
  Recommendation

Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation

5 February 2022
Xiang-jian Wang
Qian Li
Dianer Yu
Peng Cui
Zhichao Wang
Guandong Xu
    CML
ArXiv (abs)PDFHTML

Papers citing "Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation"

16 / 16 papers shown
Title
Causality and "In-the-Wild" Video-Based Person Re-ID: A Survey
Causality and "In-the-Wild" Video-Based Person Re-ID: A Survey
MD. Rashidunnabi
Kailash A. Hambarde
Hugo Proença
OODCML
45
0
0
26 May 2025
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Shiyin Tan
Dongyuan Li
Renhe Jiang
Zhen Wang
Xingtong Yu
Manabu Okumura
CML
153
0
0
20 May 2025
Causal Deconfounding via Confounder Disentanglement for Dual-Target Cross-Domain Recommendation
Causal Deconfounding via Confounder Disentanglement for Dual-Target Cross-Domain Recommendation
Jiajie Zhu
Yan Wang
Feng Zhu
Zhu Sun
CML
138
2
0
17 Apr 2024
DisenHAN: Disentangled Heterogeneous Graph Attention Network for
  Recommendation
DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation
Yifan Wang
Suyao Tang
Yuntong Lei
Weiping Song
Sheng Wang
Ming Zhang
71
141
0
21 Jun 2021
Be Causal: De-biasing Social Network Confounding in Recommendation
Be Causal: De-biasing Social Network Confounding in Recommendation
Qian Li
Xiang-jian Wang
Guandong Xu
CML
71
55
0
17 May 2021
Disentangled Graph Collaborative Filtering
Disentangled Graph Collaborative Filtering
Xiang Wang
Hongye Jin
An Zhang
Xiangnan He
Tong Xu
Tat-Seng Chua
79
546
0
03 Jul 2020
LightGCN: Simplifying and Powering Graph Convolution Network for
  Recommendation
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He
Kuan Deng
Xiang Wang
Yan Li
Yongdong Zhang
Meng Wang
GNN
189
3,650
0
06 Feb 2020
Learning Disentangled Representations for Recommendation
Learning Disentangled Representations for Recommendation
Jianxin Ma
Chang Zhou
Peng Cui
Hongxia Yang
Wenwu Zhu
CMLDRL
90
309
0
31 Oct 2019
Neural Graph Collaborative Filtering
Neural Graph Collaborative Filtering
Xiang Wang
Xiangnan He
Meng Wang
Fuli Feng
Tat-Seng Chua
187
2,981
0
20 May 2019
The Deconfounded Recommender: A Causal Inference Approach to
  Recommendation
The Deconfounded Recommender: A Causal Inference Approach to Recommendation
Yixin Wang
Dawen Liang
Laurent Charlin
David M. Blei
CML
67
73
0
20 Aug 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Rex Ying
Ruining He
Kaifeng Chen
Pong Eksombatchai
William L. Hamilton
J. Leskovec
GNNBDL
263
3,540
0
06 Jun 2018
Graph Convolutional Matrix Completion
Graph Convolutional Matrix Completion
Rianne van den Berg
Thomas Kipf
Max Welling
GNN
117
1,259
0
07 Jun 2017
node2vec: Scalable Feature Learning for Networks
node2vec: Scalable Feature Learning for Networks
Aditya Grover
J. Leskovec
186
10,876
0
03 Jul 2016
Recommendations as Treatments: Debiasing Learning and Evaluation
Recommendations as Treatments: Debiasing Learning and Evaluation
Tobias Schnabel
Adith Swaminathan
Ashudeep Singh
Navin Chandak
Thorsten Joachims
CML
162
687
0
17 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
264
12,439
0
24 Jun 2012
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